This is a working document for all the coral physiology data manipulation, analysis, and visualization of the physiology manuscript. The document includes all figures, tables, supplemental materials, methods, and results for the manuscript. Each major analysis is separated by the tabs on the left.


Potential target journals to submit:

  • Ecology
  • Journal of Experimental Biology
  • Global Change Biology
  • Others?


Principal component analyses

Methods:

Principal component analysis (PCA) (function prcomp) of scaled and centered physiological parameters (host carbohydrate, host lipid, host protein, algal endosymbiont chlorophyll a, algal endosymbiont cell density, holobiont calcification rate as previously for the same samples in Bove et al. (2019)) were employed to assess the relationship between physiological parameters and treatment conditions for each coral species. Main effects (temperature, pCO2, and reef environment) were evaluated with PERMANOVA using the adonis2 function (vegan package; version 2.5.7). An additional PERMANOVA was conducted on the combined physiology from all three species to compare species responses combined with treatments and reef environment.


Results:

Two principal components (PCs) explained approximately 66% of the variance in physiological responses of the S. siderea holobiont to ocean acidification and warming treatments (Figure 1A). PC1 was driven by differences in algal endosymbiont physiology (chlorophyll a, cell density), while PC2 represented an inverse relationship between host energy reserves (lipid, protein, carbohydrate) and calcification rates and colour intensities. Overall, lower pCO2 and temperature resulted in higher S. siderea holobiont physiology (Figure 1A). Treatment pCO2 predominantly drove S. siderea physiological responses (p < 0.001; Table S2), while temperature and reef environment were not as strong of drivers in physiological responses (p > 0.01 and p > 0.01, respectively; Table S2). For P. strigosa, 74% of the variance in the holobiont responses to treatments was explained by two PCs (Figure 1B). PC1 explained most of the variation of physiological parameters with the exception of host lipid content, which was represented in PC2. Holobiont physiology of P. strigosa was clearly reduced under warming and was generally higher in the lower pCO2 treatments (Figure 1B). Treatment temperature (p < 0.001; Table S2), pCO2 (p < 0.01; Table S2), and natal reef environment all significantly drove coral holobiont physiology (p < 0.001; Table S2). Finally, the first two PCs explained about 59% of the total variance of the P. astreoides holobiont response to treatment (Figure 1C). Coral holobiont samples separated most clearly along PC1 driven primarily by calcification rate and algal endosymbiont density, while PC2 exhibited an inverse relationship between host total carbohydrate and colour intensity. Overall, lower pCO2 drove higher P. astreoides holobiont physiology, while elevated temperature resulted in greater holobiont physiology (Figure 1C). Temperature (p < 0.001; Table S2) and pCO2 (p < 0.001; Table S2) drove separations in P. astreoides holobiont physiology, while reef environment was nonsignificant (p = 0.82; Table S2).

The first two PCs of the combined holobiont physiology explained about 62% of the total variance across samples (Figure 4). In general, fragments of S. siderea contained higher chlorophyll a content, host carbohydrate, and host lipid content, while P. strigosa fragments typically had greater host protein content accompanied with higher calcification rates, and fragments of P. astreoides were differentiated by their high symbiont densities (Figure 4A; Table S5). Despite coral species, coral holobiont physiology exhibited similar physiological responses to pCO2 and temperature treatments (Figure 4B, 4C; Table S5). As pCO2 or temperature increased, coral holobiont physiology was more constrained and exhibited similar physiological responses under stress. Further, corals from the inshore reef environment exhibited more constrained physiology than their offshore counterparts (Figure S7; Table S5).


Siderastrea siderea

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   150243 0.27232 11.4516 0.0006662 ***
## ftemp     1    24935 0.04520  5.7018 0.0053298 ** 
## reef      1    26681 0.04836  6.1009 0.0033311 ** 
## Residual 80   349861 0.63413                      
## Total    85   551720 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Pseudodiploria strigosa

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df ~ reef + fpco2 + ftemp, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## reef      1   162037 0.07959 10.9355 0.0006662 ***
## fpco2     3   196323 0.09644  4.4165 0.0019987 ** 
## ftemp     1   625389 0.30720 42.2061 0.0006662 ***
## Residual 71  1052041 0.51677                      
## Total    76  2035789 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Porites astreoides

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df ~ reef + ftemp + fpco2, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## reef      1      505 0.00150  0.1692 0.8194537    
## ftemp     1    56228 0.16639 18.8252 0.0006662 ***
## fpco2     3    96015 0.28412 10.7153 0.0006662 ***
## Residual 62   185186 0.54799                      
## Total    67   337935 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Figure 1

Figure 1. Principal component analysis (PCA) of all coral holobiont physiological parameters for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides after 93 days of exposure to different temperature and pCO2 treatments. PCAs in the top row are depicted by temperature treatment for each species (28\(^\circ\) C blue; 31\(^\circ\) C red) and the bottom row of PCAs are depicted by pCO2 for each species (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure 4

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = all_pca_df ~ fpco2 + ftemp + reef + species + ftemp:species + fpco2:species + reef:species, data = all_df, permutations = bootnum, method = "eu")
##                Df SumOfSqs      R2       F    Pr(>F)    
## fpco2           3   441584 0.08362 14.8993 0.0006662 ***
## ftemp           1    44470 0.00842  4.5014 0.0239840 *  
## reef            1    69064 0.01308  6.9908 0.0059960 ** 
## species         2  1690024 0.32003 85.5338 0.0006662 ***
## ftemp:species   2   657172 0.12444 33.2601 0.0006662 ***
## fpco2:species   6   129807 0.02458  2.1899 0.0199867 *  
## reef:species    2   134579 0.02548  6.8112 0.0006662 ***
## Residual      214  2114166 0.40034                      
## Total         231  5280867 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure 4. Principal component analysis (PCA) comparing the coral holobiont of all three species at the end of the experiment depicted by (A) species, (B) pCO2 treatment, and (C) temperature treatment. Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Correlation assessments

Methods:

Correlations of all physiological parameters were assessed to determine the relationships between parameters within each species, redargless of temperature and pCO2 treatment. The Pearson correlation coefficient (R2) of each comparison was calculated using the corrgram package (version 1.13) and the significance was calculated using the cor.test function. These relationships were then visualized through simple scatterplots.


Results:

Correlations of coral holobiont physiological parameters were generally positively related with one another across all three species. Correlations between S. siderea holobiont physiological parameters identified 15 significant relationships out of all 21 possible comparisons (Figure 2A). Of those significant correlations, six resulted in a Pearson’s correlation coefficient (R2) equal to or greater than 0.5, with the strongest relationship identified being symbiont density vs chlorophyll a (R2 = 0.72). All pairwise physiological parameters were significantly correlated with one another in P. strigosa and of those, 14 correlations exhibit moderate (R2 > 0.50) positive relationships (Figure 2B). Notably, the two strongest correlations were host carbohydrate vs host protein (R2 = 0.70) and host carbohydrate vs chlorophyll a (R2 = 0.76). Compared to both S. siderea and P. strigosa, fewer physiological traits were significantly (p < 0.05) correlated with one another in P. astreoides (12 significant out of 21 total comparisons; Figure 2C). Of the significant correlations, only two pairwise comparisons resulted in a Pearson’s correlation coefficient greater than 0.5: chlorophyll a vs colour intensity (R2 = 0.57) and host carbohydrate vs host protein (R2 = 0.68).


Figure 2

Figure 2. Coral holobiont correlation matrices (bottom panel) and scatter plots (top panel) for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides depicting pairwise comparisons of physiological parameters within each species. Strength of correlations between parameters is indicated by darker shades of blue in the bottom panel with a higher R2 value (Pearson correlation coefficient). Of these correlations, significant correlations are depicted with asterisks according to significance level (* p < 0.05; ** p < 0.01; *** p < 0.001). Scatter plots of physiological parameters are displayed in the top panel with temperature depicted by shape (28\(^\circ\)C filled points; 31\(^\circ\)C open points) and pCO2 depicted by colour (280 \(\mu\)atm light purple; 400 \(\mu\)atm dark purple; 700 \(\mu\)atm light orange; 2800 \(\mu\)atm dark orange).



Plasticity analyses

Methods:

Using PC1 and PC2 for each species, we then calculated the physiological plasticity of each experimental fragment. Plasticity was calculated as the PC distance between an experimental fragment and the control (400 \(\mu\)atm; 28\(^\circ\)C) fragment from that same colony. The effects of treatment (pCO2 and temperature) and natal reef environment on calculated distances were assessed using generalized linear models (function glm) with a Gamma distribution and log-link. The best-fit model was selected as the model with the lowest AIC for each species (Table S1). The main effects of treatment and reef environment were assessed with an ANOVA (package car; version 3.0.10) with a type III error.


Results:

Natal reef environment (p < 0.05) and pCO2 (p < 0.05) significantly altered the physiological plasticity of S. siderea (Figure 3A; Table S3, S4). Offshore fragments exhibited a positive linear trend with increasing pCO2 while the inshore fragments appear to respond in a parabolic pattern to pCO2, with the lowest calculated distances occurring at 400 \(\mu\)atm, 31\(^\circ\)C and 700 \(\mu\)atm, 28\(^\circ\)C. Plasticity of P. strigosa and P. astreoides was not significantly altered by temperature treatment, pCO2 treatment, or natal reef environment (Figure 3B, 3C; Table S3, S4). However, P. astreoides exhibited a slight trend in the inshore fragments suggesting potentially higher plasticity with increasing pCO2 that is not seen in the offshore fragments (Figure 3C).


Siderastrea siderea

## 
## Call:
## glm(formula = dist ~ reef * fpco2 + ftemp, family = Gamma(link = "log"), 
##     data = sid_dist, contrasts = list(reef = contr.sum, fpco2 = contr.sum, 
##         ftemp = contr.sum))
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.5392  -0.4066  -0.1219   0.2076   1.6019  
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   0.75433    0.08433   8.945 5.45e-13 ***
## reef1        -0.20433    0.08271  -2.470   0.0161 *  
## fpco21       -0.11652    0.14635  -0.796   0.4288    
## fpco22       -0.13498    0.18076  -0.747   0.4579    
## fpco23       -0.12823    0.13205  -0.971   0.3351    
## ftemp1       -0.02907    0.08563  -0.339   0.7353    
## reef1:fpco21  0.30174    0.14331   2.106   0.0390 *  
## reef1:fpco22 -0.24282    0.16729  -1.451   0.1514    
## reef1:fpco23 -0.04294    0.13049  -0.329   0.7431    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for Gamma family taken to be 0.4613617)
## 
##     Null deviance: 36.807  on 74  degrees of freedom
## Residual deviance: 27.862  on 66  degrees of freedom
## AIC: 254.68
## 
## Number of Fisher Scoring iterations: 6
## Analysis of Deviance Table (Type III tests)
## 
## Response: dist
## Error estimate based on Pearson residuals 
## 
##             Sum Sq Df F values  Pr(>F)  
## reef        2.7883  1   6.0436 0.01659 *
## fpco2       4.3615  3   3.1512 0.03064 *
## ftemp       0.0514  1   0.1114 0.73965  
## reef:fpco2  2.2148  3   1.6002 0.19774  
## Residuals  30.4499 66                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Pseudodiploria strigosa

## 
## Call:
## glm(formula = dist ~ reef + fpco2 + ftemp, family = Gamma(link = "log"), 
##     data = dip_dist, contrasts = list(reef = contr.sum, fpco2 = contr.sum, 
##         ftemp = contr.sum))
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -1.42095  -0.58130  -0.06819   0.29076   1.27882  
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.84433    0.09178   9.199 1.93e-13 ***
## reef1        0.04349    0.07514   0.579    0.565    
## fpco21       0.08559    0.12845   0.666    0.508    
## fpco22       0.07124    0.23272   0.306    0.760    
## fpco23      -0.11009    0.14111  -0.780    0.438    
## ftemp1      -0.03461    0.08164  -0.424    0.673    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for Gamma family taken to be 0.3908735)
## 
##     Null deviance: 27.294  on 71  degrees of freedom
## Residual deviance: 26.566  on 66  degrees of freedom
## AIC: 242.16
## 
## Number of Fisher Scoring iterations: 6
## Analysis of Deviance Table (Type III tests)
## 
## Response: dist
## Error estimate based on Pearson residuals 
## 
##            Sum Sq Df F values Pr(>F)
## reef       0.1283  1   0.3283 0.5686
## fpco2      0.4785  3   0.4081 0.7477
## ftemp      0.0675  1   0.1727 0.6791
## Residuals 25.7977 66



Porites astreoides

## 
## Call:
## glm(formula = dist ~ reef + fpco2 + ftemp, family = Gamma(link = "log"), 
##     data = por_dist, contrasts = list(reef = contr.sum, fpco2 = contr.sum, 
##         ftemp = contr.sum))
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.3919  -0.4125  -0.0464   0.2664   1.1198  
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.86006    0.07731  11.125 3.01e-15 ***
## reef1       -0.01244    0.07151  -0.174   0.8626    
## fpco21      -0.04309    0.12083  -0.357   0.7228    
## fpco22      -0.20977    0.18520  -1.133   0.2627    
## fpco23       0.08610    0.11634   0.740   0.4626    
## ftemp1      -0.15115    0.07883  -1.917   0.0608 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for Gamma family taken to be 0.2725499)
## 
##     Null deviance: 16.944  on 56  degrees of freedom
## Residual deviance: 15.563  on 51  degrees of freedom
## AIC: 188.39
## 
## Number of Fisher Scoring iterations: 5
## Analysis of Deviance Table (Type III tests)
## 
## Response: dist
## Error estimate based on Pearson residuals 
## 
##            Sum Sq Df F values  Pr(>F)  
## reef       0.0082  1   0.0300 0.86317  
## fpco2      0.6725  3   0.8225 0.48753  
## ftemp      1.0393  1   3.8133 0.05635 .
## Residuals 13.9000 51                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Figure 3

Figure 3. Assessment of physiological plasticity of (A) S. siderea, (B) P. strigosa, and (C) P. astreoides in experimental treatments and by natal reef environment. Higher values represent greater plasticity in coral holobiont samples. pCO2 treatment is depicted by colour and shape (280 \(\mu\)atm light purple, circle; 400 \(\mu\)atm dark purple, diamond; 700 \(\mu\)atm light orange, triangle; 2800 \(\mu\)atm dark orange, square) and temperature is represented as either filled (28\(^\circ\)C) or open (31\(^\circ\)C) symbols.



Supplemental Figures

Figure S1

Figure S1. Principal component analysis (PCA) of all coral holobiont physiological parameters for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides depicted by natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S2

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df_host ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2      F   Pr(>F)   
## fpco2     3    0.627 0.01852 0.5482 0.748834   
## ftemp     1    2.533 0.07483 6.6463 0.003997 **
## reef      1    0.199 0.00589 0.5229 0.582945   
## Residual 80   30.485 0.90076                   
## Total    85   33.844 1.00000                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df_symb ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   150227 0.27233 11.4523 0.0006662 ***
## ftemp     1    24933 0.04520  5.7021 0.0039973 ** 
## reef      1    26680 0.04837  6.1018 0.0039973 ** 
## Residual 80   349805 0.63411                      
## Total    85   551646 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure S2. Principal component analysis (PCA) of S. siderea coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, colour intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (280 μatm light purple; 400 μatm dark purple; 700 μatm light orange; 2800 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S3

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df_host ~ fpco2 + ftemp + reef, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   0.7317 0.04116  1.2287 0.2871419    
## ftemp     1   2.6047 0.14652 13.1213 0.0006662 ***
## reef      1   0.3469 0.01952  1.7478 0.1592272    
## Residual 71  14.0939 0.79281                      
## Total    76  17.7772 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df_symb ~ fpco2 + ftemp + reef, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   196108 0.09633  4.4119 0.0033311 ** 
## ftemp     1   619660 0.30440 41.8220 0.0006662 ***
## reef      1   167947 0.08250 11.3351 0.0013324 ** 
## Residual 71  1051979 0.51677                      
## Total    76  2035695 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure S3. Principal component analysis (PCA) of P. strigosa coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, colour intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (280 μatm light purple; 400 μatm dark purple; 700 μatm light orange; 2800 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S4

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df_host ~ fpco2 + ftemp + reef, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2      F  Pr(>F)  
## fpco2     3   1.7463 0.13595 3.4824 0.01865 *
## ftemp     1   0.4610 0.03589 2.7580 0.10060  
## reef      1   0.2740 0.02133 1.6394 0.20053  
## Residual 62  10.3638 0.80682                 
## Total    67  12.8452 1.00000                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df_symb ~ fpco2 + ftemp + reef, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   100597 0.29771 11.2278 0.0006662 ***
## ftemp     1    51174 0.15144 17.1348 0.0006662 ***
## reef      1      969 0.00287  0.3245 0.6875416    
## Residual 62   185165 0.54798                      
## Total    67   337905 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure S4. Principal component analysis (PCA) of P. asteroides coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, colour intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (280 μatm light purple; 400 μatm dark purple; 700 μatm light orange; 2800 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S5

Figure S5. Mean (\(\pm\)SE) physiological parameter (each row) measured for (A) S. siderea, (B) P. strigosa, (C) P. astreoides, and (D) U. tenuifolia at the completion of the 93-day experimental period.



Figure S6

Figure S6. Coral colour changes over the experimental period. Representative images of fragments of (A) P. astreoides, (B) S. siderea, and (C) P. strigosa from the same colonies demonstrating change in coral colour over time in either control (400 μatm; 28 °C) or warming (400 μatm; 31 °C) treatments from the start of the experiment (T0) to the end (T90).



Figure S7

Figure S7. Principal component analysis (PCA) comparing the coral holobiont of all three species at the end of the experiment depicted reef environment. Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S8



Supplemental Tables

Table S1

Table S1. Model performance comparisons of generalized linear models (GLM) for plasticity assessments to select the best-fit model per species using the package performance (version 0.7.0). Akaike information criterion (AIC) was used to select the best-fit model per species. The performance score computes indices of model performance for all models per species at once for comparison across models.
Model formula AIC BIC Nagelkerke R2 Performance score
Siderastrea Siderea
reef environment * pCO2 + temperature 254.68 277.86 0.2899 85.5
reef environment * (pCO2 + temperature) 256.41 281.91 0.2928 74.3
reef environment + pCO2 + temperature 254.78 271.01 0.2213 71.9
reef environment + pCO2 * temperature 256.46 277.32 0.2483 64.7
reef environment * pCO2 * temperature 260.35 295.11 0.3346 55.3
pCO2 + temperature 259.43 273.33 0.1381 21.3
Pseudodiploria strigosa
reef environment * pCO2 * temperature 242.52 276.67 0.2401 68.6
reef environment + pCO2 * temperature 239.68 260.17 0.1249 66.1
pCO2 + temperature 240.53 254.19 0.0263 39.5
reef environment * (pCO2 + temperature) 244.19 269.24 0.1179 30.9
reef environment + pCO2 + temperature 242.16 258.10 0.0319 27.7
reef environment * pCO2 + temperature 244.67 267.43 0.0833 17.3
Porites astreoides
reef environment * pCO2 + temperature 193.32 213.75 0.1116 62.2
pCO2 + temperature 186.42 198.68 0.0925 60.0
reef environment * (pCO2 + temperature) 195.32 217.79 0.1116 53.9
reef environment + pCO2 + temperature 188.39 202.70 0.0931 52.6
reef environment + pCO2 * temperature 192.03 210.41 0.0995 49.6
reef environment * pCO2 * temperature 200.97 229.58 0.1174 40.0




Table S2

Table S2. PERMANOVA model output from each species using the adonis2 function with 1500 iterations.
Df Sum of Squares R2 F P-value
Siderastrea Siderea
pCO2 3 150243 0.272 11.45 0.00067
temperature 1 24935 0.045 5.70 0.00533
reef environment 1 26681 0.048 6.10 0.00333
Residual 80 349861 0.634
Total 85 551720 1.000
Pseudodiploria strigosa
reef environment 1 162037 0.080 10.94 0.00067
pCO2 3 196323 0.096 4.42 0.00200
temperature 1 625389 0.307 42.21 0.00067
Residual 71 1052041 0.517
Total 76 2035789 1.000
Porites astreoides
reef environment 1 505 0.001 0.17 0.81945
temperature 1 56228 0.166 18.83 0.00067
pCO2 3 96015 0.284 10.72 0.00067
Residual 62 185186 0.548
Total 67 337935 1.000




Table S3

Table S3. GLM output from plasticity assessments for each species. The intercept of each model was set as 300 \(\mu\)atm, 28\(^\circ\)C, and inshore reef environment.
Estimate Standard error Statistic P-value
Siderastrea Siderea
(Intercept) 0.754 0.084 8.94 0.000
reef environment (offshore) -0.204 0.083 -2.47 0.016
pCO2-current -0.117 0.146 -0.80 0.429
pCO2-EOC -0.135 0.181 -0.75 0.458
pCO2-extreme -0.128 0.132 -0.97 0.335
temperature (31C) -0.029 0.086 -0.34 0.735
reef environment (offshore):pCO2-current 0.302 0.143 2.11 0.039
reef environment (offshore):pCO2-EOC -0.243 0.167 -1.45 0.151
reef environment (offshore):pCO2-extreme -0.043 0.130 -0.33 0.743
Pseudodiploria strigosa
(Intercept) 0.844 0.092 9.20 0.000
reef environment (offshore) 0.043 0.075 0.58 0.565
pCO2-current 0.086 0.128 0.67 0.508
pCO2-EOC 0.071 0.233 0.31 0.760
pCO2-extreme -0.110 0.141 -0.78 0.438
temperature (31C) -0.035 0.082 -0.42 0.673
Porites astreoides
(Intercept) 0.860 0.077 11.12 0.000
reef environment (offshore) -0.012 0.072 -0.17 0.863
pCO2-current -0.043 0.121 -0.36 0.723
pCO2-EOC -0.210 0.185 -1.13 0.263
pCO2-extreme 0.086 0.116 0.74 0.463
temperature (31C) -0.151 0.079 -1.92 0.061




Table S4

Table S4. Type III test of analysis of deviance output based on the plasticity GLM per species in Table S3.
Sum of Squares Df F values P-value
Siderastrea Siderea
reef environment 2.79 1 6.0 0.02
pCO2 4.36 3 3.2 0.03
temperature 0.05 1 0.1 0.74
reef environment:pCO2 2.21 3 1.6 0.20
Residuals 30.45 66
Pseudodiploria strigosa
reef environment 0.13 1 0.3 0.57
pCO2 0.48 3 0.4 0.75
temperature 0.07 1 0.2 0.68
Residuals 25.80 66
Porites astreoides
reef environment 0.01 1 0.0 0.86
pCO2 0.67 3 0.8 0.49
temperature 1.04 1 3.8 0.06
Residuals 13.90 51




Table S5

Table S5. PERMANOVA model output across species using the adonis2 function with 1500 iterations.
Df Sum of Squares R2 F P-value
pCO2 3 441584 0.084 14.90 0.00067
temperature 1 44470 0.008 4.50 0.02398
reef environment 1 69064 0.013 6.99 0.00600
species 2 1690024 0.320 85.53 0.00067
temperature:species 2 657172 0.124 33.26 0.00067
pCO2:species 6 129807 0.025 2.19 0.01999
reef environment:species 2 134579 0.025 6.81 0.00067
Residual 214 2114166 0.400
Total 231 5280867 1.000




Table S6

Table S6. PERMANOVA model output of coral host or algal symbiont physiology per species using the adonis2 function with 1500 iterations depicted in Figures S2-S4.
Coral host
Algal symbionts
Df Sum of Squares R2 F P-value Df Sum of Squares R2 F P-value
Siderastrea Siderea
pCO2 3 1 0.019 0.55 0.74883 3 150227 0.272 11.45 0.00067
temperature 1 3 0.075 6.65 0.00400 1 24933 0.045 5.70 0.00400
reef environment 1 0 0.006 0.52 0.58294 1 26680 0.048 6.10 0.00400
Residual 80 30 0.901 80 349805 0.634
Total 85 34 1.000 85 551646 1.000
Pseudodiploria strigosa
pCO2 3 1 0.041 1.23 0.28714 3 196108 0.096 4.41 0.00333
temperature 1 3 0.147 13.12 0.00067 1 619660 0.304 41.82 0.00067
reef environment 1 0 0.020 1.75 0.15923 1 167947 0.083 11.34 0.00133
Residual 71 14 0.793 71 1051979 0.517
Total 76 18 1.000 76 2035695 1.000
Porites astreoides
pCO2 3 2 0.136 3.48 0.01865 3 100597 0.298 11.23 0.00067
temperature 1 0 0.036 2.76 0.10060 1 51174 0.151 17.13 0.00067
reef environment 1 0 0.021 1.64 0.20053 1 969 0.003 0.32 0.68754
Residual 62 10 0.807 62 185165 0.548
Total 67 13 1.000 67 337905 1.000




Session information

Session information from the last run date on 2021-06-01:

## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Catalina 10.15.7
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] car_3.0-10         carData_3.0-4      png_0.1-7          MASS_7.3-53       
##  [5] performance_0.7.0  wesanderson_0.3.6  RColorBrewer_1.1-2 gridGraphics_0.5-1
##  [9] corrplot_0.84      Hmisc_4.4-2        Formula_1.2-4      survival_3.2-7    
## [13] magick_2.5.2       ggpubr_0.4.0       vroom_1.3.2        lmerTest_3.1-3    
## [17] lme4_1.1-26        Matrix_1.3-2       kableExtra_1.3.1   finalfit_1.0.2    
## [21] ggfortify_0.4.11   cowplot_1.1.1      Rmisc_1.5          shiny_1.5.0       
## [25] vegan_2.5-7        lattice_0.20-41    permute_0.9-5      forcats_0.5.0     
## [29] stringr_1.4.0      purrr_0.3.4        tibble_3.0.4       tidyverse_1.3.0   
## [33] plotly_4.9.3       openxlsx_4.2.3     corrgram_1.13      tidyr_1.1.2       
## [37] ggbiplot_0.55      scales_1.1.1       plyr_1.8.6         dplyr_1.0.2       
## [41] ggplot2_3.3.3      broom_0.7.3        readr_1.4.0        knitr_1.33        
## 
## loaded via a namespace (and not attached):
##   [1] readxl_1.3.1        backports_1.2.1     lazyeval_0.2.2     
##   [4] splines_3.6.3       digest_0.6.27       foreach_1.5.1      
##   [7] htmltools_0.5.1     fansi_0.4.1         magrittr_2.0.1     
##  [10] checkmate_2.0.0     cluster_2.1.0       see_0.6.2          
##  [13] modelr_0.1.8        jpeg_0.1-8.1        colorspace_2.0-0   
##  [16] ggrepel_0.9.0       rvest_0.3.6         haven_2.3.1        
##  [19] xfun_0.22           crayon_1.3.4        jsonlite_1.7.2     
##  [22] iterators_1.0.13    glue_1.4.2          registry_0.5-1     
##  [25] gtable_0.3.0        webshot_0.5.2       abind_1.4-5        
##  [28] DBI_1.1.0           rstatix_0.6.0       Rcpp_1.0.5         
##  [31] viridisLite_0.3.0   xtable_1.8-4        htmlTable_2.1.0    
##  [34] foreign_0.8-75      bit_4.0.4           htmlwidgets_1.5.3  
##  [37] httr_1.4.2          ellipsis_0.3.1      mice_3.13.0        
##  [40] farver_2.0.3        pkgconfig_2.0.3     nnet_7.3-14        
##  [43] dbplyr_2.0.0        effectsize_0.4.1    labeling_0.4.2     
##  [46] tidyselect_1.1.0    rlang_0.4.11        later_1.1.0.1      
##  [49] munsell_0.5.0       cellranger_1.1.0    tools_3.6.3        
##  [52] cli_2.2.0           generics_0.1.0      ggridges_0.5.3     
##  [55] evaluate_0.14       fastmap_1.0.1       yaml_2.2.1         
##  [58] bit64_4.0.5         fs_1.5.0            zip_2.1.1          
##  [61] nlme_3.1-151        mime_0.10           xml2_1.3.2         
##  [64] compiler_3.6.3      rstudioapi_0.13     curl_4.3.1         
##  [67] ggsignif_0.6.0      reprex_0.3.0        statmod_1.4.35     
##  [70] stringi_1.5.3       parameters_0.10.1   highr_0.8          
##  [73] nloptr_1.2.2.2      vctrs_0.3.6         pillar_1.4.7       
##  [76] lifecycle_0.2.0     insight_0.13.1      data.table_1.13.6  
##  [79] seriation_1.2-9     httpuv_1.5.5        R6_2.5.0           
##  [82] latticeExtra_0.6-29 promises_1.1.1      TSP_1.1-10         
##  [85] gridExtra_2.3       rio_0.5.16          codetools_0.2-18   
##  [88] boot_1.3-25         assertthat_0.2.1    withr_2.3.0        
##  [91] bayestestR_0.8.0    mgcv_1.8-33         parallel_3.6.3     
##  [94] hms_1.0.0           rpart_4.1-15        minqa_1.2.4        
##  [97] rmarkdown_2.6       numDeriv_2016.8-1.1 lubridate_1.7.9.2  
## [100] base64enc_0.1-3